BACKGROUND Saliva represents a promising non-invasive source of novel biomarkers for diagnosis and prognosis cancer. This meta-analysis evaluates the diagnostic value of salivary biomarkers for detection of malignant non-oral tumors to better define the value of saliva as an alternative liquid biopsy. MATERIALS AND METHODS We performed a systematic review and meta-analysis. PubMed, Embase, LILACS and the Cochrane Library were searched to identify articles that examined the potential of salivary biomarkers for the diagnosis of malignant non-oral tumors. To assess the overall accuracy, we calculated the diagnostic odds ratio (DOR), area under hierarchical summary receiver operating characteristic (AUC) curve, sensitivity, specificity, positive likelihood ratio (PLR) and negative likelihood ratio (NLR) using a random- or fixed-effects model. Heterogeneity and publication bias were assessed. Statistical tests were two-sided. RESULTS One hundred fifty-five study units from twenty-nine articles with 11,153 subjects were included. The pooled sensitivity, specificity, PLR, NLR, DOR and AUC were 0.76 (95% confidence intervals (CI), 0.74 to 0.77), 0.76 (95% CI, 0.75 to 0.77), 3.22 (95% CI, 2.92 to 3.55), 0.31 (95% CI, 0.28 to 0.34), 13.42 (95% CI, 12.28 to 15.96) and 0.85 (95% CI, 0.84 to 0.87), respectively. CONCLUSIONS Salivary biomarkers may be potentially used for non-invasive diagnosis of malignant non-oral tumors. Key messagesThis meta-analysis evaluates the diagnostic value of salivary biomarkers for detection of malignant non-oral tumors to better define the role of saliva as an alternative liquid biopsy.Salivary biomarkers showed 85% accuracy for cancer distant to the oral cavity.Saliva represents a promising non-invasive source of novel biomarkers in cancer.Determination of the optimum pH in a coupled enzyme assay poses significant challenges because altering the pH of the reaction mixture can affect the performance of both enzymes. Here, we demonstrate a simple and reliable method to determine the pH optimum for pyruvate kinase using the pyruvate kinase/lactate dehydrogenase coupled enzyme assay. This simple and reliable method can be broadly adapted to determine the pH optimum for various enzymes that are assayed using a coupled enzyme assay.Introduction Compared to Staphylococcus aureus, coagulase-negative staphylococci (CoNS) are characterized by a lower capacity to cause acute, live-threatened infections. CoNS are, however, of ever increasing importance as pathogens causing infections in immunocompromised patients and after foreign-material implantation. Typically, antibiotics fail to cure foreign body-related infections and removal of the implanted device is inevitable.Areas covered This review focuses on the emergence of CoNS species, their pathogenic potential in particular due to their ability to form therapy-refractory biofilms on biotic and abiotic surfaces and evasion strategies to resist host response and antibiotic treatment. Their medical significance and proven and novel therapy strategies are discussed.Expert opinion CoNS contribute significantly to morbidity and socio-economic costs. The anticipated developments in modern medicine, in particular the increasing use of foreign materials and the rising numbers of immunocompromised patients, as well as the changing demographic and hospital-related factors will inevitably contribute to further emergence of CoNS infections. https://www.selleckchem.com/products/torin-1.html Increasing rates of (multi-)resistant CoNS strains will limit the therapeutic armamentarium and aggravate treatment strategies. Increased research is necessary to understand their role as resistance and virulence gene reservoir and to reduce CoNS infections by the development of innovative colonization-preventing materials and other CoNS-tailored treatment strategies.Introduction There is increasing recognition of the need for deprescribing of inappropriate medications in older adults. However, efforts to encourage implementation of deprescribing in clinical practice have resulted in mixed results across settings and countries.Area covered Searches were conducted in PubMed, Embase, and Google Scholar in June 2019. Reference lists, citation checking, and personal reference libraries were also utilized. Studies capturing the main challenges of, and opportunities for, implementing deprescribing into clinical practice across selected health-care settings internationally, and international deprescribing-orientated policies were included and summarized in this narrative review.Expert opinion Deprescribing intervention studies are inherently heterogeneous because of the complexity of interventions employed and often do not reflect the real-world. Further research investigating enhanced implementation of deprescribing into clinical practice and across health-care settings is required. Process evaluations in deprescribing intervention studies are needed to determine the contextual factors that are important to the translation of the interventions in the real-world. Deprescribing interventions may need to be individually tailored to target the unique barriers and opportunities to deprescribing in different clinical settings. Introduction of national policies to encourage deprescribing may be beneficial, but need to be evaluated to determine if there are any unintended consequences.Hierarchical organization of brain function has been an established concept in the neuroscience field for a long time, however, it has been rarely demonstrated how such hierarchical macroscale functional networks are actually organized in the human brain. In this study, to answer this question, we propose a novel methodology to provide an evidence of hierarchical organization of functional brain networks. This article introduces the hybrid spatiotemporal deep learning (HSDL), by jointly using deep belief networks (DBNs) and deep least absolute shrinkage and selection operator (LASSO) to reveal the temporal hierarchical features and spatial hierarchical maps of brain networks based on the Human Connectome Project 900 functional magnetic resonance imaging (fMRI) data sets. Briefly, the key idea of HSDL is to extract the weights between two adjacent layers of DBNs, which are then treated as the hierarchical dictionaries for deep LASSO to identify the corresponding hierarchical spatial maps. Our results demonstrate that both spatial and temporal aspects of dozens of functional networks exhibit multiscale properties that can be well characterized and interpreted based on existing computational tools and neuroscience knowledge.